Data Center Quality Engineer
@ Google

Pryor, OK
$170,000
On Site
Full Time
Posted 22 days ago

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Job Details

Overview

The Data Center Quality Engineer at Google is responsible for ensuring quality and manufacturing excellence in cloud hardware technology and electronic systems.

Minimum Qualifications

Bachelor's degree in Computer Science, Computer Engineering, Mechanical, Electrical, Industrial, Materials or a related Engineering discipline; 8 years of experience in quality, manufacturing, or product engineering; advanced statistical methodologies expertise (DOE, SPC, six sigma, FMEA, ANOVA, MSA, Fishbone); and ability to travel up to 20% as needed.

Preferred Qualifications

Master's degree or PhD in relevant engineering fields; Certified Reliability/Quality Engineer certification or similar experience; experience in manufacturing assembly processes, product launches, process optimization, technical leadership, project management, and data analysis/visualization using SQL, JMP, R, Matlab, Tableau, PowerBI or Python.

About the Job

Be part of a team pushing boundaries with custom silicon solutions powering future Google products. Work on the next generation of hardware experiences. Contribute to drive product performance through data-driven decisions and continuous improvement in manufacturing processes.

Responsibilities

  • Define and execute data collection for complex technical issues.
  • Drive design, optimization, and qualification of manufacturing processes.
  • Analyze manufacturing/field data from data center environments.
  • Present performance metrics and insights to stakeholders clearly.
  • Create and update technical documentation based on data and feedback.

Key skills/competency

  • quality
  • manufacturing
  • process optimization
  • data analysis
  • statistical methods
  • technical documentation
  • SQL
  • Python
  • DOE
  • FMEA
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How to Get Hired at Google

🎯 Tips for Getting Hired

  • Customize your resume: Highlight relevant engineering and quality skills.
  • Research Google: Understand their culture and innovation focus.
  • Showcase analytics expertise: Emphasize experience with statistical tools.
  • Prepare for technical interviews: Review manufacturing and process optimization topics.

📝 Interview Preparation Advice

Technical Preparation

Review advanced statistical methods and DOE fundamentals.
Brush up on manufacturing process optimization techniques.
Practice SQL, Python, and data visualization tools.
Study cloud hardware system technical documentation.

Behavioral Questions

Describe a challenging process optimization instance.
Explain conflict resolution in cross-functional teams.
Share experiences leading technical projects.
Discuss handling continuous improvement feedback.

Frequently Asked Questions